# AI Candidate Matcher - Resume vs Job Description (`hirelayer/candidate-matcher`) Actor

Score resumes against a job description with an explanation for every criterion. Send resume files or texts; criteria are extracted from the job for you. Pay per matched candidate.

- **URL**: https://apify.com/hirelayer/candidate-matcher.md
- **Developed by:** [HireLayer](https://apify.com/hirelayer) (community)
- **Stats:** 3 total users, 2 monthly users, 100.0% runs succeeded, 0 bookmarks
- **User rating**: No ratings yet

## Pricing

from $50.00 / 1,000 matched candidates

This Actor is paid per event. You are not charged for the Apify platform usage, but only a fixed price for specific events.

Learn more: https://docs.apify.com/actors/running/actors-in-store.md#pay-per-event

## What's an Apify Actor?

An Actor is a serverless cloud program that runs on the Apify platform. It has two run modes.
In Batch mode, an Actor accepts a well-defined JSON input, performs an action which can take anything from a few seconds to a few hours,
and optionally produces a well-defined JSON output, datasets with results, or files in key-value store.
In Standby mode, an Actor provides a web server which can be used as a website, API, or an MCP server.

Apify vocabulary and the platform model are defined once, in the agent quickstart at https://apify.com/agents.md.

## How to integrate an Actor?

If asked about integration, you help developers integrate Actors into their projects.
You adapt to their stack and deliver integrations that are safe, well-documented, and production-ready.

Do not guess an integration path. Every one of them is in the agent quickstart at https://apify.com/agents.md: the Apify MCP server, Agent Skills with the Apify CLI, the JavaScript and Python clients, the REST API, and the account-free path for an agent with no human to sign in. It also carries the rule on stating cost before the first paid run.

For examples already wired to this Actor's own input schema, see the [API](#api) section below.

Each client library has reference documentation the quickstart does not restate: [JavaScript/TypeScript](https://docs.apify.com/api/client/js/docs.md) (`npm install apify-client`) and [Python](https://docs.apify.com/api/client/python/docs.md) (`pip install apify-client`).

# README

### What does AI Candidate Matcher do?

**AI Candidate Matcher** scores candidates against a job description and explains every score:

- a **score** from 0 to 1 for each candidate,
- a short **summary** of the fit,
- for **each criterion**: whether it is clearly met (`ideal`), partly met (`potential`), not mentioned (`not_mentioned`) or contradicted (`not_valid`), with the evidence found in the resume.

Send **resume files** (PDF, Word, images…) or resume **texts**. You do not need criteria: they are extracted from the job description for you, or you can pass your own.

Resumes and job descriptions can be in any language.

It is powered by the [HireLayer](https://hirelayer.co) recruiting API. Processing runs in the EU.

### Why use it?

- **Screen a pile of applications in minutes**, with a reason for every score that a recruiter can check.
- **Same criteria for every candidate**: fair, comparable scores.
- **Hard requirements stay visible**: filter on `is_mandatory` and `match_status` to reject candidates who miss one.
- **Pay per candidate**: no subscription.

### How to use it

1. Click **Try for free**.
2. Paste the job description.
3. Add resume URLs (one per line) and/or candidates as text.
4. Click **Start** and open the **Matches** table, sorted by score.

### Input

| Field | Description |
| --- | --- |
| `jobDescription` | The job description (required). |
| `resumeUrls` | Public URLs of resume files. Each file is parsed first. |
| `candidates` | Candidates as text: `[{"id": "c1", "text": "…"}]`, or `{"id": "c2", "resumeUrl": "…"}`. |
| `matchingCriteria` | Optional criteria, as returned by the [Job Description Criteria Extractor](https://apify.com/hirelayer/job-criteria-extractor). |
| `maxConcurrency` | Candidates processed at the same time (default 3). |

```json
{
  "jobDescription": "Senior Frontend Engineer. 5+ years frontend, React and TypeScript in production, fluent English. Nice to have: Next.js.",
  "candidates": [{ "id": "c1", "text": "Jane Doe. Frontend developer, 7 years React and TypeScript at Acme. English native." }]
}
```

### Output

One dataset item per candidate:

```json
{
  "candidate_id": "c1",
  "candidate_name": null,
  "status": "success",
  "score": 0.857,
  "summary": "Jane Doe possède une solide expérience de 7 ans en React/TypeScript…",
  "evaluated_criteria": [
    {
      "id": "crit_1",
      "label": "Expérience de 5 ans ou plus en développement frontend avec React et TypeScript en production",
      "weight": 3,
      "is_mandatory": true,
      "match_status": "ideal",
      "match_explanation": "Le CV indique clairement 7 ans d’expérience avec React et TypeScript en production…"
    }
  ]
}
```

The criteria used are saved in the `MATCHING_CRITERIA` record of the key-value store, so you can reuse them in the next run. A candidate that cannot be processed gives an item with `"status": "error"` and is not charged.

### Pricing

- **$0.05 per matched candidate**
- **$0.05 per job description** when the criteria are extracted for you (once per run)
- **$0.08 per resume file** parsed (candidates sent as text are not parsed)

Set a maximum cost per run in the run options: the Actor stops before going over it.

### Use it from code

```bash
curl -X POST "https://api.apify.com/v2/acts/hirelayer~candidate-matcher/run-sync-get-dataset-items?token=YOUR_APIFY_TOKEN" \
  -H "Content-Type: application/json" \
  -d '{"jobDescription": "…", "resumeUrls": ["https://example.com/resume.pdf"]}'
```

The Actor is also available to AI agents through the [Apify MCP server](https://docs.apify.com/platform/integrations/mcp).

### FAQ

**How is the score computed?** It is the weighted average of the criteria: `ideal` counts 1, `potential` 0.6, `not_mentioned` 0.5 and `not_valid` 0. See the [HireLayer Match documentation](https://hirelayer.co/api-docs/match).

**Should the score decide alone?** No. Scores help recruiters prioritise; hiring decisions stay with people.

**Need help?** Open an issue in the **Issues** tab or write to contact@hirelayer.co.

# Actor input Schema

## `jobDescription` (type: `string`):

The full job description, in any language (up to 50,000 characters).

## `resumeUrls` (type: `array`):

Public URLs of resume files, one per line. Each file is parsed first (charged as a parsed resume).

## `candidates` (type: `array`):

Optional. Candidates whose resume you already have as plain text: \[{"id": "c1", "text": "..."}]. You can also pass {"id": "c2", "resumeUrl": "https://..."}. IDs must be unique.

## `matchingCriteria` (type: `array`):

Optional. Criteria to evaluate, as returned by the Job Description Criteria Extractor: \[{"id", "label", "weight" (1-3), "is_mandatory", "rationale"}]. Leave empty to extract them from the job description.

## `maxConcurrency` (type: `integer`):

How many items are processed at the same time.

## Actor input object example

```json
{
  "jobDescription": "Senior Frontend Engineer (React / TypeScript) - Remote, Europe\n\nWe are looking for a senior frontend engineer to build our recruiting platform.\n\nRequirements:\n- 5+ years of professional frontend development\n- Strong React and TypeScript experience in production\n- Fluent English\n\nNice to have:\n- Next.js\n- Experience with design systems",
  "resumeUrls": [
    "https://hirelayer.co/benchmark/resume-parser-2026-10/cv2-two-page-en.pdf",
    "https://hirelayer.co/benchmark/resume-parser-2026-10/cv5-infographic-en.pdf"
  ],
  "candidates": [],
  "maxConcurrency": 3
}
```

# Actor output Schema

## `results` (type: `string`):

One item per candidate: score, summary and per-criterion evaluation.

## `criteria` (type: `string`):

The criteria used for this run, ready to reuse.

# API

You can run this Actor programmatically using our API. Below are code examples in JavaScript, Python, and CLI, as well as the OpenAPI specification and MCP server setup.

## JavaScript example

```javascript
import { ApifyClient } from 'apify-client';

// Initialize the ApifyClient with your Apify API token
// Replace the '<YOUR_API_TOKEN>' with your token
const client = new ApifyClient({
    token: '<YOUR_API_TOKEN>',
});

// Prepare Actor input
const input = {
    "jobDescription": `Senior Frontend Engineer (React / TypeScript) - Remote, Europe

We are looking for a senior frontend engineer to build our recruiting platform.

Requirements:
- 5+ years of professional frontend development
- Strong React and TypeScript experience in production
- Fluent English

Nice to have:
- Next.js
- Experience with design systems`,
    "resumeUrls": [
        "https://hirelayer.co/benchmark/resume-parser-2026-10/cv2-two-page-en.pdf",
        "https://hirelayer.co/benchmark/resume-parser-2026-10/cv5-infographic-en.pdf"
    ],
    "candidates": []
};

// Run the Actor and wait for it to finish
const run = await client.actor("hirelayer/candidate-matcher").call(input);

// Fetch and print Actor results from the run's dataset (if any)
console.log('Results from dataset');
console.log(`💾 Check your data here: https://console.apify.com/storage/datasets/${run.defaultDatasetId}`);
const { items } = await client.dataset(run.defaultDatasetId).listItems();
items.forEach((item) => {
    console.dir(item);
});

// 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/js/docs

```

## Python example

```python
from apify_client import ApifyClient

# Initialize the ApifyClient with your Apify API token
# Replace '<YOUR_API_TOKEN>' with your token.
client = ApifyClient("<YOUR_API_TOKEN>")

# Prepare the Actor input
run_input = {
    "jobDescription": """Senior Frontend Engineer (React / TypeScript) - Remote, Europe

We are looking for a senior frontend engineer to build our recruiting platform.

Requirements:
- 5+ years of professional frontend development
- Strong React and TypeScript experience in production
- Fluent English

Nice to have:
- Next.js
- Experience with design systems""",
    "resumeUrls": [
        "https://hirelayer.co/benchmark/resume-parser-2026-10/cv2-two-page-en.pdf",
        "https://hirelayer.co/benchmark/resume-parser-2026-10/cv5-infographic-en.pdf",
    ],
    "candidates": [],
}

# Run the Actor and wait for it to finish
run = client.actor("hirelayer/candidate-matcher").call(run_input=run_input)

# Fetch and print Actor results from the run's dataset (if there are any)
print(f"💾 Check your data here: https://console.apify.com/storage/datasets/{run.default_dataset_id}")
for item in client.dataset(run.default_dataset_id).iterate_items():
    print(item)

# 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/python/docs/quick-start

```

## CLI example

```bash
echo '{
  "jobDescription": "Senior Frontend Engineer (React / TypeScript) - Remote, Europe\\n\\nWe are looking for a senior frontend engineer to build our recruiting platform.\\n\\nRequirements:\\n- 5+ years of professional frontend development\\n- Strong React and TypeScript experience in production\\n- Fluent English\\n\\nNice to have:\\n- Next.js\\n- Experience with design systems",
  "resumeUrls": [
    "https://hirelayer.co/benchmark/resume-parser-2026-10/cv2-two-page-en.pdf",
    "https://hirelayer.co/benchmark/resume-parser-2026-10/cv5-infographic-en.pdf"
  ],
  "candidates": []
}' |
apify call hirelayer/candidate-matcher --silent --output-dataset

```

## MCP server setup

```json
{
    "mcpServers": {
        "apify": {
            "type": "http",
            "url": "https://mcp.apify.com/?tools=fetch-actor-details,hirelayer/candidate-matcher"
        }
    }
}
```

The hosted server signs you in with OAuth on first connect, so no API token belongs in this config. Clients without OAuth support can send an `Authorization: Bearer <APIFY_API_TOKEN>` header instead, using a token from API & Integrations in Apify Console (https://console.apify.com/settings/integrations).

## OpenAPI specification

Download the OpenAPI definition: https://api.apify.com/v2/actors/JokMEMHbdOTBelacv/builds/Naxl6LzjvPf3h9b3h/openapi.json